Project/Area Number |
17K12704
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Research Category |
Grant-in-Aid for Young Scientists (B)
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Allocation Type | Multi-year Fund |
Research Field |
Cognitive science
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Research Institution | Toho University (2018-2019) Tokyo Denki University (2017) |
Principal Investigator |
|
Project Period (FY) |
2017-04-01 – 2020-03-31
|
Project Status |
Completed (Fiscal Year 2019)
|
Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2018: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
Fiscal Year 2017: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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Keywords | 神経同期 / 神経回路モデル / Border Ownership / 図方向決定 / 視覚的注意 / 視覚情報処理 / 図領域統合 / 神経細胞同期発火 / 注意選択 / 神経回路ネットワークモデル / Border-Ownership / 同期発火 / NMDAシナプス / 脳型階層構造 / 選択的注意 / 計算論的神経科学 |
Outline of Final Research Achievements |
The activity of a border ownership selective (BOS) neuron underlies the perception of a figure. Previous work has proposed that this grouping mechanism is implemented by population of grouping (“G”) cells and that these G-cells also serve as “handles” for attention. Experimental studies have investigated correlations between BOS neurons. A previous study showed that modulatory common feedback may underlie the synchrony between BOS neurons with consistent BOS, i.e. when both neurons in the pair respond to the same object. Here, I extended this model to explain synchrony observed between neurons with non-consistent BOS. In my model, the responses of BOS neurons are modulated by the activity of G-cells mediating spatial-attention and object-based attention. The G-cells provide modulatory feedback to BOS neurons via NMDA receptors. Simulation results for the model suggest that the interactions between feedback signals play a critical role to modulate the activities of BOS neurons.
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Academic Significance and Societal Importance of the Research Achievements |
サルV2のニューロンが、図方向(Border Ownership, BO)に対して選択性を持つことが知られている(BOS細胞)。最近、皮質において、空間的に離れて配置されたBOS細胞の同期発火が、物体知覚の皮質表現である可能性が示唆された。しかし、空間的に離れて配列されたBOS細胞が同期するための神経回路メカニズムは、生理実験的な検証が困難であり、その詳細も未知であった。本研究が提案する神経回路モデルにより、この問題への解法の示唆が与えられた。この結果は、生物の視覚処理メカニズムの理解だけでなく、コンピュータビジョンアルゴリズムの発展に寄与することが期待される。
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